Revision 0a03bbb7cf19e479dc77592ed09621eeb8afb470 authored by A.I. McLeod on 21 December 2015, 08:55:04 UTC, committed by cran-robot on 21 December 2015, 08:55:04 UTC
1 parent 83deceb
DLSimulate.Rd
\name{DLSimulate}
\alias{DLSimulate}
\title{ Simulate linear time series }
\description{
The Durbin-Levinsion recursions are used to simulate a stationary
time series given an unit innovation sequence and given autocovariance
function. Requires \deqn{O(n^2)} flops.
}
\usage{
DLSimulate(n, r, useC = TRUE, rand.gen = rnorm, ...)
}

\arguments{
\item{n}{ length of time series to be generated }
\item{r}{ autocovariances, lags 0, ...,  }
\item{useC}{ =TRUE, use C interface. Otherwise direct
computation. }
\item{rand.gen}{ random number generator to use}
\item{\dots}{ optional arguments passed to \code{rand.gen} }
}
\details{
See Hipel and McLeod (1994) or
McLeod, Yu and Krougly (2007).
}
\value{
simulated time series of length n
}
\references{
McLeod, A.I., Yu, Hao, Krougly, Zinovi L.  (2007).
Algorithms for Linear Time Series Analysis,
Journal of Statistical Software.
}
\author{ A.I. McLeod }

\seealso{
}
\examples{
#Simulate hyperbolic decay time series
#with Hurst coefficient, H=0.9
n<-2000
H<-0.9
alpha<-2*(1-H)  #hyperbolic decay parameter
r<-(1/(1:n))^alpha
z<-DLSimulate(n, r)
plot.ts(z)
#can use HurstK function in FGN library to estimate H

}
\keyword{ ts }
\keyword{ datagen }


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